INITIALIZING

System // Dark Hour

PYTHON / PYTORCH / C++ / FASTAPI / SQL / OPENGL / SCIKIT-LEARN / PYTHON / PYTORCH / C++ / FASTAPI / SQL / OPENGL / SCIKIT-LEARN / PYTHON / PYTORCH / C++ / FASTAPI / SQL / OPENGL / SCIKIT-LEARN / PYTHON / PYTORCH / C++ / FASTAPI / SQL / OPENGL / SCIKIT-LEARN / PYTHON / PYTORCH / C++ / FASTAPI / SQL / OPENGL / SCIKIT-LEARN / PYTHON / PYTORCH / C++ / FASTAPI / SQL / OPENGL / SCIKIT-LEARN / PYTHON / PYTORCH / C++ / FASTAPI / SQL / OPENGL / SCIKIT-LEARN / PYTHON / PYTORCH / C++ / FASTAPI / SQL / OPENGL / SCIKIT-LEARN / PYTHON / PYTORCH / C++ / FASTAPI / SQL / OPENGL / SCIKIT-LEARN / PYTHON / PYTORCH / C++ / FASTAPI / SQL / OPENGL / SCIKIT-LEARN / PYTHON / PYTORCH / C++ / FASTAPI / SQL / OPENGL / SCIKIT-LEARN / PYTHON / PYTORCH / C++ / FASTAPI / SQL / OPENGL / SCIKIT-LEARN / PYTHON / PYTORCH / C++ / FASTAPI / SQL / OPENGL / SCIKIT-LEARN / PYTHON / PYTORCH / C++ / FASTAPI / SQL / OPENGL / SCIKIT-LEARN / PYTHON / PYTORCH / C++ / FASTAPI / SQL / OPENGL / SCIKIT-LEARN / PYTHON / PYTORCH / C++ / FASTAPI / SQL / OPENGL / SCIKIT-LEARN / PYTHON / PYTORCH / C++ / FASTAPI / SQL / OPENGL / SCIKIT-LEARN / PYTHON / PYTORCH / C++ / FASTAPI / SQL / OPENGL / SCIKIT-LEARN / PYTHON / PYTORCH / C++ / FASTAPI / SQL / OPENGL / SCIKIT-LEARN / PYTHON / PYTORCH / C++ / FASTAPI / SQL / OPENGL / SCIKIT-LEARN /
PYTHON / PYTORCH / C++ / FASTAPI / SQL / OPENGL / SCIKIT-LEARN / PYTHON / PYTORCH / C++ / FASTAPI / SQL / OPENGL / SCIKIT-LEARN / PYTHON / PYTORCH / C++ / FASTAPI / SQL / OPENGL / SCIKIT-LEARN / PYTHON / PYTORCH / C++ / FASTAPI / SQL / OPENGL / SCIKIT-LEARN / PYTHON / PYTORCH / C++ / FASTAPI / SQL / OPENGL / SCIKIT-LEARN / PYTHON / PYTORCH / C++ / FASTAPI / SQL / OPENGL / SCIKIT-LEARN / PYTHON / PYTORCH / C++ / FASTAPI / SQL / OPENGL / SCIKIT-LEARN / PYTHON / PYTORCH / C++ / FASTAPI / SQL / OPENGL / SCIKIT-LEARN / PYTHON / PYTORCH / C++ / FASTAPI / SQL / OPENGL / SCIKIT-LEARN / PYTHON / PYTORCH / C++ / FASTAPI / SQL / OPENGL / SCIKIT-LEARN / PYTHON / PYTORCH / C++ / FASTAPI / SQL / OPENGL / SCIKIT-LEARN / PYTHON / PYTORCH / C++ / FASTAPI / SQL / OPENGL / SCIKIT-LEARN / PYTHON / PYTORCH / C++ / FASTAPI / SQL / OPENGL / SCIKIT-LEARN / PYTHON / PYTORCH / C++ / FASTAPI / SQL / OPENGL / SCIKIT-LEARN / PYTHON / PYTORCH / C++ / FASTAPI / SQL / OPENGL / SCIKIT-LEARN / PYTHON / PYTORCH / C++ / FASTAPI / SQL / OPENGL / SCIKIT-LEARN / PYTHON / PYTORCH / C++ / FASTAPI / SQL / OPENGL / SCIKIT-LEARN / PYTHON / PYTORCH / C++ / FASTAPI / SQL / OPENGL / SCIKIT-LEARN / PYTHON / PYTORCH / C++ / FASTAPI / SQL / OPENGL / SCIKIT-LEARN / PYTHON / PYTORCH / C++ / FASTAPI / SQL / OPENGL / SCIKIT-LEARN /
03Even Steven: Regularization Analysis

Overview

Built a configurable Multi-Layer Perceptron (MLP) framework for image classification on the Google Quick, Draw! dataset. Evaluated multiple regularization techniques to study overfitting and generalization.

Key Features

  • Implemented Dropout, L2 Weight Decay, Batch Normalization, and Data Augmentation
  • Analyzed training and validation curves
  • Improved test accuracy from 85.04% to 87.14%
View Source Code

Architecture

DATASET
REGULARIZATION
TRAINING/VALIDATION
87.14% ACCURACY

Technologies

PyTorchNumPyMatplotlib
2026
System Online